Building Sentiment Predictor --Exercise
Building Sentiment Predictor Exercise
In this example exercise, you will modify the Building Sentiment Workflow and try different Machine Learning algorithms and compute its performance using ROC Curve and Scorer node.
To begin with, data has been partitioned for you as in the original workflow. Your task is to try different Learner nodes and monitor each of its performance by using its corresponding Predictor node and find its accuracy.
- Can you tell which algorithm performed better than SVM?
- Which algorithm is trained faster?
Nodes
- CSV Reader3 ×
- Bag Of Words Creator2 ×
- Dictionary Filter2 ×
- Dictionary Tagger2 ×
- Term To String2 ×
- Case Converter1 ×
- Column Filter1 ×
- Document Data Extractor1 ×
- Document Vector1 ×
- Duplicate Row Filter1 ×
- GroupBy1 ×
- Model Writer1 ×
- N Chars Filter1 ×
- Number Filter1 ×
- Partitioning1 ×
- Porter Stemmer1 ×
- Punctuation Erasure1 ×
- Row Splitter1 ×
- Stop Word Filter1 ×
- Strings To Document1 ×
- TF1 ×
- Table Creator1 ×
Extensions
Links
- No links available